Browsing Arthur (Articles) by UP Author "Bekker, Andriette, 1958-"

Browsing Arthur (Articles) by UP Author "Bekker, Andriette, 1958-"

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  • Alternative dirichlet priors for estimating entropy via a power sum functional 
    Botha, Tanita; Ferreira, Johannes Theodorus; Bekker, Andriette, 1958- (MDPI, 2021-06-25)
    Entropy is a functional of probability and is a measurement of information contained in a system; however, the practical problem of estimating entropy in applied settings remains a challenging and relevant problem. The ...
  • Capturing a change in the covariance structure of a multivariate process 
    Bekker, Andriette, 1958-; Ferreira, Johannes Theodorus; Human, Schalk William; Adamski, Karien (MDPI, 2022-01-13)
    This research is inspired from monitoring the process covariance structure of q attributes where samples are independent, having been collected from a multivariate normal distribution with known mean vector and unknown ...
  • Coming together of Bayesian inference and skew spherical data 
    Nakhaei Rad, Najmeh; Bekker, Andriette, 1958-; Arashi, Mohammad; Ley, Christophe (Frontiers Media S.A., 2022-02-08)
    This paper presents Bayesian directional data modeling via the skew-rotationally-symmetric Fisher-von Mises-Langevin (FvML) distribution. The prior distributions for the parameters are a pivotal building block in Bayesian ...
  • Compositional data modeling through dirichlet innovations 
    Makgai, Seitebaleng Littah; Bekker, Andriette, 1958-; Arashi, Mohammad (MDPI, 2021-10-03)
    The Dirichlet distribution is a well-known candidate in modeling compositional data sets. However, in the presence of outliers, the Dirichlet distribution fails to model such data sets, making other model extensions ...
  • Empowering differential networks using Bayesian analysis 
    Smith, Jarod; Arashi, Mohammad; Bekker, Andriette, 1958- (Public Library of Science, 2022-01-25)
    Differential networks (DN) are important tools for modeling the changes in conditional dependencies between multiple samples. A Bayesian approach for estimating DNs, from the classical viewpoint, is introduced with a ...
  • Enhancing wind direction prediction of South Africa wind energy hotspots with Bayesian mixture modeling 
    Rad, Najmeh Nakhaei; Bekker, Andriette, 1958-; Arashi, Mohammad (Nature Research, 2022-07-06)
    Wind energy production depends not only on wind speed but also on wind direction. Thus, predicting and estimating the wind direction for sites accurately will enhance measuring the wind energy potential. The uncertain ...
  • Mastering the body and tail shape of a distribution 
    Wagener, Matthias; Bekker, Andriette, 1958-; Arashi, Mohammad (MDPI, 2021-10-20)
    The normal distribution and its perturbation have left an immense mark on the statistical literature. Several generalized forms exist to model different skewness, kurtosis, and body shapes. Although they provide better ...
  • Matrix-variate beta generator - developments and application 
    Van Niekerk, Janet; Bekker, Andriette, 1958-; Arashi, Mohammad (Iranian Statistical Society, 2021-04-03)
    Matrix-variate beta distributions are applied in di erent fields of hypothesis testing, multivariate correlation analysis, zero regression, canonical correlation analysis and etc. Amethodology is proposed to generate ...
  • Mobius transformation-induced distributions provide better modelling for protein architecture 
    Arashi, Mohammad; Nakhaei Rad, Najmeh; Bekker, Andriette, 1958-; Schubert, Wolf-Dieter (MDPI, 2021-10-29)
    Proteins are found in all living organisms and constitute a large group of macromolecules with many functions. Proteins achieve their operations by adopting distinct three-dimensional structures encoded within the sequence ...
  • Tsallis and other generalised entropy forms subject to Dirichlet mixture priors 
    Ferreira, Johannes Theodorus; Botha, Tanita; Bekker, Andriette, 1958- (MDPI, 2022-05-28)
    Entropy indicates a measure of information contained in a complex system, and its estimation continues to receive ongoing focus in the case of multivariate data, particularly that on the unit simplex. Oftentimes the ...